Search

This paper examines the impact of external monitoring by financial analysts and institutional investors on managers' decisions regarding using upward earnings management and downward earnings guidance to meet or beat analysts' forecasts. I find that firms followed by more unaffiliated financial analysts are less likely to manage earnings upwards but more likely to guide analysts' forecasts downwards. I also find firms held to a greater extent by transient institutional investors are more likely to manage earnings upwards and less likely to guide analysts' forecasts downwards, while firms held to a greater extent by dedicated institutional investors are less likely to engage in upward earnings management. The results indicate that managers' trade-offs between upward earnings management and downward earnings guidance to meet or beat analysts' forecasts vary with external monitoring and with the characteristics of the parties that serve as external monitors.

This study provides insight into how CMIP5 climate models perform in simulating summer and winter precipitation at different geographical locations and climate conditions. Precipitation biases in the CMIP5 historical (1951-2005) simulations relative to the Climatic Research Unit (CRU) observations are evaluated over 8 regions exhibiting distinct seasonal hydro-climates: moist tropical (Amazonia and central Africa); monsoonal (southern China); moist continental (central Europe); semi-arid (western United States and eastern Australia); and polar (Siberia and Canada). While the bias and mean quantile bias (MQB, defined herein) reflect no substantial differences in CMIP5 summer and winter precipitation simulations at the global scale, strong seasonality and high inter-model variability are found over the selected moist tropical regions. In the semi-arid regions, high inter-model precipitation variability is also displayed, especially in summer. In Siberia and central Europe, most CMIP5 models underestimate summer precipitation, and overestimate it in winter. Also, the MQB values decrease as the choice of quantile thresholds increase. While the CMIP5 models exhibit similar behaviors in simulating high latitude winter precipitation, they differ substantially in summer simulations for the selected Canadian and Siberian regions. In the monsoonal southern China region, CMIP5 models exhibit large overall precipitation biases in both summer and winter, as well as at higher quantiles. Finally, the CMIP5 precipitation simulations are also tested with the University of Delaware observation data and trend of the results are found to be the same.

The edgy, lyrical verse of an essential voice from the China