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Non-standard errors
(2021)
In statistics, samples are drawn from a population in a data-generating process (DGP). Standard errors measure the uncertainty in sample estimates of population parameters. In science, evidence is generated to test hypotheses in an evidence-generating process (EGP). We claim that EGP variation across researchers adds uncertainty: non-standard errors. To study them, we let 164 teams test six hypotheses on the same sample. We find that non-standard errors are sizeable, on par with standard errors. Their size (i) co-varies only weakly with team merits, reproducibility, or peer rating, (ii) declines significantly after peer-feedback, and (iii) is underestimated by participants.
In this study, we develop a technique for estimating a firm’s expected cost of equity capital derived from analyst consensus forecasts and stock prices. Building on the work of Gebhardt/Lee/-Swaminathan (2001) and Easton/Taylor/Shroff/Sougiannis (2002), our approach allows daily estimation, using only publicly available information at that date. We then estimate the expected cost of equity capital at the market, industry and individual firm level using historical German data from 1989-2002 and examine firm characteristics which are systematically related to these estimates. Finally, we demonstrate the applicability of the concept in a contemporary case study for DaimlerChrysler and the European automobile industry.
Our study provides evidence on the share price reactions to the announcement of equity issues in Germany, where capital market is characterized by institutional features distinct from the U.S. market. German seasoned equity issues yield a positive market reaction which contrasts to the significant negative abnormal returns reported for the U.S. We provide evidence that these results are due to differences in both issuing characteristics and floatation methods, and in the corporate governance and ownership structures of the two countries. Our study explains much of the empirical puzzle of different market reactions to seemingly similar events across financial markets.