Accounting Research Journal

Bias, stability, and predictive ability in the measurement of systematic risk : Table of Contents

Stephen Gray, Jason Hall, Drew Klease, Alan McCrystal — Sat Nov 28 08:00:19 GMT 2009

Abstract:
Purpose – Estimates of systematic risk or beta are an important determinant of the cost of capital. The standard technique used to compile beta estimates is an ordinary least squares regression of stock returns on market returns using four to five years of monthly data. This convention assumes that a longer time series of data will not adequately capture risks associated with existing assets. This paper seeks to address this issue. Design/methodology/approach – Each year from 1980 to 2004, equity betas are estimated for 1,717 Australian firms over periods of four to 45 years, and form equal value portfolios of high, medium and low beta stocks. The paper compares expected returns – derived from the capital asset pricing model (CAPM) and subsequent realised market returns – and actual returns over subsequent annual and four-year periods. Findings – The paper shows that the ability of beta estimates to predict future stock returns systematically increases with the length of the estimation window and when the Vasicek bias correction is applied. However, estimation error is insignificantly different from that associated with a naïve assumption that beta equals one for all stocks. Research limitations/implications – The implication is that using all available returns data in beta estimation, along with the Vasicek bias correction, reduces the imprecision of expected returns estimates derived from the CAPM. A limitation of the method is the use of conditional realised returns as a proxy for expected returns, given that it is not possible directly to observe expected returns incorporated into share prices. Originality/value – The paper contributes to the understanding of corporate finance practitioners and academics, who routinely use beta estimates derived from ordinary least squares regression.

Management control systems: a model for R&D units : Table of Contents

Parulian Silaen, Robert Williams — Sat Nov 28 08:00:19 GMT 2009

Abstract:
Purpose – The purpose of this paper is to develop a proposal for a new conceptual framework for management control systems (MCS) in R&D units. Design/methodology/approach – The paper is a descriptive study that reviews the control literature and proposes an MCS framework in the light of four key elements: desired ends, actors, control implementation, and control tools. Findings – The study found two sub-elements of desired ends (directional and yardstick) to be complementary in a low level of uncertainty, while directional should be emphasized more in a high level of uncertainty. Five sub-elements of actors are used differently along the levels of uncertainty. The timing and use of formal and informal control types are found to be different regarding the level of uncertainty. Finally, the dimension and the value of control tools are used differently in those two distinctive situations. Research limitations/implications – The paper is limited to a descriptive study that may have further implication for research by using the framework to investigate the MCS applied by R&D units. Practical implications – The four key elements of MCS may be used in practice by developing a detail measure of each element to suit the condition of the unit. Originality/value – The paper is a new way of looking at MCS, broadening the comprehension, and introducing new MCS key elements.

The impact of different types of ownership concentration on annual report voluntary disclosures in New Zealand : Table of Contents

Haiyan Jiang, Ahsan Habib — Sat Nov 28 08:00:19 GMT 2009

Abstract:
Purpose – The purpose of this paper is to investigate the impact of different categories of ownership concentration on corporate voluntary disclosure practices in New Zealand. Design/methodology/approach – The study applies panel data regression analysis to a sample of New Zealand listed companies from 2001 to 2005. Two-stage least squares analysis (2SLS) is conducted. Ownership concentration is categorised into four mutually exclusive ownership structures. Findings – The paper finds that firm-year observations characterised by financial institution-controlled ownership structure tends to make significantly fewer (more) disclosures at high (low) concentration levels supporting expropriation. In contrast, firm-year observations in the high (low) concentration group with government- and management-controlled ownership structures exhibit considerably higher (lower) voluntary disclosure scores, suggesting a positive monitoring effect at high ownership concentration level. Research limitations/implications – The results provide evidence for the proposition that the efficiency of large block holders' monitoring varies with the level of ownership concentration. Practical implications – To promote transparency in capital markets, regulators can encourage or discourage certain types of large shareholding, while monitoring the level of ownership concentration by means of regulation. Investors, especially less sophisticated retail investors, will benefit from the findings that different ownership groups affect disclosure policies differently. Originality/value – The findings strengthen the importance of differentiating ownership structures into various classes to infer the real impact of differential controlling properties on managerial disclosure decisions. Furthermore, the results reveal that the relationship between ownership concentration and voluntary disclosure practices has a non-linear pattern.

The effects of forecast specificity on the asymmetric short-window share market response to management earnings forecasts : Table of Contents

Howard Chan, Robert Faff, Yee Kee Ho, Alan Ramsay — Sat Nov 28 08:00:19 GMT 2009

Abstract:
Purpose – This study aims to test the effects of forecast specificity on the asymmetric short-window share market response to management earnings forecasts (MEF). Design/methodology/approach – The paper examines a large sample of hand-checked Australian data over the period 1994 to 2001. Using an analyst news benchmark, it estimates a series of regressions to investigate whether the short-term impact from bad news announcements is greater in magnitude than from good news announcements and whether this differs between routine and non-routine MEFs. Additionally, it examines whether (after controlling for news content of MEF) there is a differential market impact conditional on specificity: minimum versus maximum versus range versus point. Findings – The results indicate that an asymmetric response is evident for the overall sample and a sub-set of non-routine forecasts. Contrary to predictions, the results show that forecast specificity, minimum, maximum, range and point MEFs make no additional contribution to the differences in the market reaction to bad or good news. Originality/value – The study extends the research investigating the short-run market impact of MEFs. The main element of innovation derives from the interaction between specificity and news content, as well as distinguishing between routine versus non-routine cases. Notably, it found little support for the view that more specific forecasts elicit greater market responses. What the results do suggest is that managers appear to choose the form of the forecast to suit the news being delivered. In particular, bad news delivered in a minimum forecast seems to be ignored by the market.