Abstract

Many prior works have already investigated what sagacious managers’ incentives on selective/opportunistic management forecasts disclosures such as managerial job securities at risk (Brochet, F., Faurel, L., McVay, S., 2011), corporations wounding up and bankruptcies in high, the probability of anti-takeover by outsiders on rising (Morck et al., 1990; Brennan, 1999), executive compensations upside down (Miller and Piotroski, 2000; Nagar et al., 2003; Bebchuk and Grinstein, 2005), litigation risk likely in danger (Miller and Piotroski, 2000; Brown et al., 2005; Rogers and Stocken, 2005), proprietary costs no longer going down (Verrecchia, 2001 and Dye, 2001), firm performance in downward (Miller, 2002) and even inside trading (Cheng and Lo, 2006; Rogers and Stocken, 2005) are. In additional to those, this paper incrementally contributes to precedented management forecasts literature. However, to my knowledge, this probably is first paper to document that cunning managers likely tempt to disclose management earnings forecasts outside in bias when they face the struggling fiscal condition credit ratings nearly to be downgraded by credit rating agencies such as Moody's, S&P and Fitch Ratings. When firms are potentially facing enormous pressure of financial distress from credit raters proxied by crediting ratings likely to be downgraded and managers also predict their firm performance will be improved in forthcoming, because they hold more insider information relative to outsiders, thereby being more likely to voluntarily deliver forecast disclosures outside reducing the degree of uncertainty of information asymmetry, especially good-news forecasts, to alleviate public's nerves about a plump for corporate credit ratings though influencing the recessive perception of credit rating agencies. Therefore, this can fill in this gap in prior management forecast archives. Jung, Soderstrom and Yang (2013) argue that shrewd managers attempt to alter credit ratings agencies' perceptions towards companies worsening borrowing creditability through long-term earnings smoothing activities (i.e. reduction in earnings volatility across horizons). Smoothing techniques include that managers change their accounting disclosing policies by releasing more good-news revenue and better-than-expect earnings forecasts to public prior to credit ratings being slumped/bumped. Furthermore, it also tremendously contributes to voluntary disclosure literature in as much as it can provide additional empirical evidence to support the relation between corporate voluntary disclosures and crediting ratings after controlling macroeconomic, institutional factors and other fixed effects.This paper uses S&P 1500 firms in testing periods to examine the relation between management forecast policy and firm financial distress proxied by credit ratings. Using S&P 1500 firms as those firms' market value can cover over 80% of the U.S. market capitalization and the reasons of those firm higher coverage by financial analysts, to prevent biased-collection from database. In this paper, I examine how downgrade risks of credit ratings the managers faced influence management earnings forecast policy i.e. whether firms with currently facing downgrade risk of their credit ratings and that in concurrent with the condition that being forecast to have better future performance, managers of those are likely to issue good-news management guidance and whether those firms will have a change in cost of debts after their management forecast policy being changed in prior period. More importantly, this paper will deal with the results potentially suffering from the endogeneity/simultaneity through 2 stage regressions to estimate the like hood in upside down possibility of credit ratings & 3 stage regressions to estimate both Management forecast incentives and like hood in change in credit ratings, thereby finding the effect of like hood of downward of credit ratings on change in managers' forecast incentives and the effect of the managers' forecast incentive on corporate cost of capital.

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