A model of trading in speculative markets is developed based on differences of opinion among traders. Our purpose is to explain some of the empirical regularities that have been documented concerning the relationship between volume and price and the time-series properties of price and volume. We assume that traders share common prior beliefs and receive common information but differ in the way in which they interpret this information. Some results are that absolute price changes and volume are positively correlated, consecutive price changes exhibit negative serial correlation, and volume is positively autocorrelated.

Reviews the book "Dictionary of Business and Industry," by Robert J. Schwartz.

We study the effect of hearing cases alongside female judicial colleagues on the probability that a federal judge hires a female law clerk. Federal judges are assigned to judicial panels at random and have few limitations on their choices of clerks. Using a unique dataset of federal case records merged with judicial hiring information, we find a significant effect of the fraction of copanelists who are female on a male judge’s likelihood of hiring a female clerk. This finding suggests that increases in the diversity of the upper rungs of a profession can create opportunities at the entry level.

Two forms of expertise can influence audit quality: industry and task-specific expertise. Anecdotal evidence suggests that tax knowledge is task-specific, rather than industryspecific and audit offices with increased exposure to complex tax issues develop this taskspecific expertise. Using outcomes related to audits of the income tax accounts, we examine whether tax task-specific knowledge (TSK) affects the audit quality of the income tax accounts and find that tax TSK increases the audit quality of the income tax accounts. We also find evidence of an improved response to misstatements among audit offices with tax TSK, demonstrated by a decreased likelihood of future tax misstatements following the disclosure of a tax restatement. Finally, we observe the effect of tax TSK among audit offices with lower levels of auditor-provided tax services (APTS). This result suggests that audit offices without the benefit of knowledge spillover from APTS rely more on the tax TSK.

The unprecedented contagion of the SARS-CoV-2 virus, causative of COVID-19, has spawned watershed economic, social, ethical, and political upheaval—catalyzing severe polarization among the global populace. Ostensibly, to demonstrate the most appropriate path towards responding to the virus outbreak, public officials in the United States (“U.S.”), representing both Democratic and Republican parties, stand accused of unduly influencing COVID-19 records in their respective jurisdictions. This study investigates the role political partisanship may have played in decreasing the accuracy of publicly reported COVID-19 data in the U.S. Leveraging social identity theory, we contend that public officials may have manipulated the reporting records in accounting for COVID-19 infection cases and deaths to validate the effectiveness of political party objectives. We employ Benford's Law to assess misreporting and evaluate the integrity of county-level COVID-19 reporting data through the construction of four distinct political party classifications. Specifically, we cross the county voting majority for the 2016 presidential candidate for each U.S. state (Democratic and Republican) with the 2020 gubernatorial political party (Democratic and Republican) in which each county resides. For the sample period of January 21, 2020 through November 3, 2020 (Election Day), the study's results suggest that the reported COVID-19 infection cases and deaths in the U.S. violate Benford's Law in a manner consistent with underreporting. Our analysis reveals that Democratic counties demonstrate the smallest departures from Benford's Law while Republican counties demonstrate the greatest departures.