Conservative accounting and linear information valuation models

Prior research using the residual income valuation model and linear information models has generally found that estimates of firm value are negatively biased. We argue that this could result from the way in which accounting conservatism effects are reflected in such models. We build on the conservative accounting model of Feltham and Ohlson (1995) and the Dechow, Hutton and Sloan (1999) (DHS) methodology to propose a valuation model that includes a conservatism-correction term, based on the properties of past realizations of residual income and other information. Other information is measured using analyst-forecast-based predictions of residual income. We use data comparable to the DHS sample to compare the bias and inaccuracy of value estimates from our model and from models similar to those used by DHS and Myers (1999). Valuation biases are substantially less negative for our model, but valuation inaccuracy is not markedly reduced

Unequal Impact of Conservatism on Accrual Measures and Drivers: Implications for the Specification of Accrual Models

This study makes two main contributions to the literature. Firstly, it tests empirically the relative timeliness of accrual measures and earnings components used as explanatory variables in accrual models (“accrual drivers”) regarding the impact of conservatism. Secondly, taking into account the empirical evidence on such a timeliness, it discusses intuitively potential implications for the specification of (traditional) accrual models and the quality of discretionary accrual estimates. It concludes that common accrual models, as Jones (1991), are misspecified. They have a dependent variable (accruals) asymmetrically affected by conservatism, and one or more explanatory variables that are not affected, inducing a non-systematic measurement error in estimating discretionary accruals.accruals; accrual models; discretionary accruals; conservatism.

Low gravity phase separator

An apparatus is described for phase separating a gas-liquid mixture as might exist in a subcritical cryogenic helium vessel for cooling a superconducting magnet at low gravity such as in planetary orbit, permitting conservation of the liquid and extended service life of the superconducting magnet

A multiple scales approach to sound generation by vibrating bodies

The problem of determining the acoustic field in an inviscid, isentropic fluid generated by a solid body whose surface executes prescribed vibrations is formulated and solved as a multiple scales perturbation problem, using the Mach number M based on the maximum surface velocity as the perturbation parameter. Following the idea of multiple scales, new 'slow' spacial scales are introduced, which are defined as the usual physical spacial scale multiplied by powers of M. The governing nonlinear differential equations lead to a sequence of linear problems for the perturbation coefficient functions. However, it is shown that the higher order perturbation functions obtained in this manner will dominate the lower order solutions unless their dependence on the slow spacial scales is chosen in a certain manner. In particular, it is shown that the perturbation functions must satisfy an equation similar to Burgers' equation, with a slow spacial scale playing the role of the time-like variable. The method is illustrated by a simple one-dimenstional example, as well as by three different cases of a vibrating sphere. The results are compared with solutions obtained by purely numerical methods and some insights provided by the perturbation approach are discussed

THE DETERMINANTS OF THE GOING PUBLIC DECISION: EVIDENCE FROM THE U.K.

Several theoretical papers have addressed the question of why firms raise public equity. However, direct empirical evidence on the characteristics of firms going public is scarce and limited to non-Anglo-Saxon contexts. Our research combines the analysis of ex ante and ex post characteristics of Initial Public Offering (IPO) companies to cast more light on the determinants of the going public decision in the UK. Some of our findings are consistent with prior empirical studies in other contexts: IPO probability depends positively on firm size and stock price levels. Results also suggest that a firm?s need to finance investments is not the main motive to go public, although this reason underlies the going public decision in a number of UK firms. Besides, contrary to the evidence shown by Pagano et al. (1998) for Italian IPOs, we find that UK firms do not go public to reduce debt since leverage is negatively related to the probability of going public. Finally, the relationship between profitability and the likelihood of an IPO for our whole IPO sample is negative and significant. Whether firms that go public have higher investment rates than other firms, as is the case of our survivor IPOs, the negative effect of profitability on the probability of going public may reflect the fact that these firms cannot yield sufficient internal funds to finance large investments. In fact, the relationship between profitability and the likelihood of an IPO becomes significantly positive for our acquired IPO group, where investment opportunities variables have no significant effect on the going public decision. This result is consistent with the portfolio rebalancing motive to go public.Initial Public Offerings, the Going Public Decision.

Piecewise Linear Accrual Models: do they really control for the asymmetric recognition of gains and losses?

The asymmetric recognition of gains and losses underlying conservative accounting is not taken into account by Jones (1991)-type accrual models. Recently, Moreira (2002) and Ball and Shivakumar (2005a) have proposed piecewise linear accrual models designed to control for this asymmetric impact. Our paper first discusses the sign of the expected measurement error in discretionary accruals (DAC) estimates when models do not control for the asymmetry underlying conservatism. We find that DAC in firms with bad news (BN) are expected to be understated, while those in good news (GN) firms will be overstated. Based on this original result we empirically test, using graphical and statistical tools, whether piecewise linear accrual models correct such a measurement error. The empirical evidence shows mixed results. For GN firms the estimates are corrected downwards, as expected; for BN firms, unexpectedly, part of the estimates is also corrected downwards. The reason for this unexpected result seems to lie in a non-linear relationship between accruals and the proxy for BN that the models are unable to control for. Thus, DAC estimates under piecewise linear models are not deemed to be of better quality than those of traditional accrual models.accrual models; piecewise linear accrual models; conservatism; earnings management

Earnings Management to Avoid Losses: a cost of debt explanation

In this paper we analyze firms’ earnings management behavior to avoid losses conditional on the (asymmetric) incentive underlying market (positive/negative) returns. Our intuition is that firms with negative returns in the period (bad news, BN) face a higher incentive to undertake earnings management, and that their ultimate intention is to hide from credit markets a signal (loss) that could be translated into a negative impact on their cost of debt. The empirical evidence supports this intuition. BN firms show higher earnings management pervasiveness than their counterparts with good news (GN), and the set with simultaneous BN and prior period positive earnings undertake more pervasive earnings manipulation than BN firms in general. Within this restricted set of firms, and consistent with a cost of debt explanation, we find that firms with larger needs of debt show a higher incidence of earnings management to avoid losses. The overall empirical evidence challenges the implicit assumption in Burgstahler and Dichev (1997) that the incentive to manage earnings is homogeneous to all firms, and suggests that the discontinuities around zero in the earnings distributions are driven, at least partly, by firms’ earnings management behavior.earnings management, earnings thresholds, earnings discontinuities, cost of debt

Unlocking the Secrets of Ancient Writing. The Parallel Lives of Michael Ventris and Linda Schele and the Decipherment of Mycenaean and Mayan Writing

Catalogue of an exhibition conducted in conjunction with the Eleventh International Mycenological Colloquium held at the University of Texas at Austin in 2000. This program features brief histories of the CIPEM Mycenological conferences and PASP, followed by comparative retrospectives on both Michael Ventris, who deciphered Linear B, and Linda Schele, who performed a similar feat for Mayan glyphs.Classic

Are analysts' loss functions asymmetric?

Recent research by Gu and Wu (2003) and Basu and Markov (2004) suggests that the well-known optimism bias in analysts? earnings forecasts is attributable to analysts minimizing symmetric, linear loss functions when the distribution of forecast errors is skewed. An alternative explanation for forecast bias is that analysts have asymmetric loss functions. We test this alternative explanation. Theory predicts that if loss functions are asymmetric then forecast error bias depends on forecast error variance, but not necessarily on forecast error skewness. Our results confirm that the ex ante forecast error variance is a significant determinant of forecast error and that, after controlling for variance, the sign of the coefficient on forecast error skewness is opposite to that found in prior research. Our results are consistent with financial analysts having asymmetric loss functions. Further analysis reveals that forecast bias varies systematically across style portfolios formed on book-to-price and market capitalization. These firm characteristics capture systematic variation in forecast error variance and skewness. Within style portfolios, forecast error variance continues to play a dominant role in explaining forecast error.

Are analysts? loss functions asymmetric?

Recent research by Gu and Wu (2003) and Basu and Markov (2004) suggests that the well-known optimism bias in analysts? earnings forecasts is attributable to analysts minimizing symmetric, linear loss functions when the distribution of forecast errors is skewed. An alternative explanation for forecast bias is that analysts have asymmetric loss functions. We test this alternative explanation. Theory predicts that if loss functions are asymmetric then forecast error bias depends on forecast error variance, but not necessarily on forecast error skewness. Our results confirm that the ex ante forecast error variance is a significant determinant of forecast error and that, after controlling for variance, the sign of the coefficient on forecast error skewness is opposite to that found in prior research. Our results are consistent with financial analysts having asymmetric loss functions. Further analysis reveals that forecast bias varies systematically across style portfolios formed on book-to-price and market capitalization. These firm characteristics capture systematic variation in forecast error variance and skewness. Within style portfolios, forecast error variance continues to play a dominant role in explaining forecast error.