Complexity is never simple: Intangible intensity and analyst accuracy
We examine the relationship between intangible intensity and the accuracy of analyst forecasts. Using an international sample of 2,200 firms during 2000–2016, we show that analyst accuracy decreases significantly when intangible intensity grows. In exploring the determinants of this effect, we disti...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Institución: | Universidad Autónoma de Madrid |
| Repositorio: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglés |
| OAI Identifier: | oai:repositorio.uam.es:10486/695400 |
| Acceso en línea: | http://hdl.handle.net/10486/695400 https://dx.doi.org/10.1177/2340944420931871 |
| Access Level: | acceso abierto |
| Palabra clave: | Accuracy of analyst forecasts cost of equity governance mechanisms intangible intensity Economía |
| Sumario: | We examine the relationship between intangible intensity and the accuracy of analyst forecasts. Using an international sample of 2,200 firms during 2000–2016, we show that analyst accuracy decreases significantly when intangible intensity grows. In exploring the determinants of this effect, we distinguish between firm risk and the risk associated with intangibles. Our results reveal the role of financial reporting quality, ownership structure, and institutional quality in moderating the relationship between intangible intensity and analyst accuracy. Analyst forecast accuracy acts as a channel through which the higher levels of information asymmetry associated with intangible intensity affect the cost of equity. Our results are robust to different intangible intensity measures; mandatory changes in financial reporting standards; the implementation of transparency rules in certain industry sectors; and financial crisis periods. We have devised alternative econometric tools that deal with potential sample selection bias and the dynamics of our empirical model. |
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