Use of Fuller's Technique to Reduce Measurement Error in the Returns/Earnings Association

Empirical estimates of the earnings response coefficient have consistently been lower than theory predicts. This may be because empirical proxies for unexpected earnings contain measurement error. I demonstrate and evaluate the use of a recently developed technique by Fuller that yields consistent parameter estimates in the presence of measurement error. The empirical results indicate that this technique is successful at mitigating measurement error bias in the earnings response coefficient. The earnings response coefficient increases by as much as 52%. In contrast, replication of the techniques performed in previous studies increases the earnings response coefficient by only 8%.     

Systematic Measurement Error in the Estimation of Discretionary Accruals: An Evaluation of Alternative Modelling Procedures

This paper evaluates the extent of predictable measurement error induced by five alternative approaches to the estimation of discretionary accruals. The source and magnitude of the error is assessed by reference to the strength of the association between the discretionary accrual estimate and proxies for the non-discretionary components of total accruals. Results indicate that discretionary accruals generated by the Healy model are associated with the highest level of predictable measurement error. While the remaining four models generate significantly lower error levels, the magnitude of error remains highly significant. Findings highlight the limitations of existing models and emphasise the need for further developments in relation to the measurement of earnings management activity.     

Consistent Analyst Expectation Error and Earnings Management: Evidence from China

Using data from the Chinese A-share market in 2004–12, we show how cognitive bias of individual analysts led to counterproductive effect in less-developed financial markets. We form an ex ante measure of analysts’ expectation error, a measure suitable for markets with a short history. We find that star analysts tend to be more optimistic than ordinary analysts, and their biased opinions influence other analysts because of analyst herding behavior. Two-stage least square regression results suggest that consistent expectation errors among analysts can lead to earnings management. These insights are valuable to investors and regulators.     

Assessing the Efficiency of an Insurance Provider—A Measurement Error Approach

The purpose of this paper is to compare the cost efficiency of private and public property insurance providers in Switzerland. The most commonly used measure for this kind of exercise is the claims-premium ratio. We argue that this measure may give strongly biased results. We develop a simple model to test whether the elasticity of premiums with respect to claims is less than unity. We address the fact that premium income is relatively stable across time, while claims are not, using estimation techniques that correct for measurement error. We develop tools to cope with heteroskedasticity in such measurement errors and apply the model to a data set on 19 firms in housing insurance markets in Switzerland. We show that the public insurance providers are about 20% more cost efficient than their private counterparts.JEL Classification No.: C21, D21, L84     

Accounting Conservatism and the Relation Between Returns and Accounting Data

This study adds change in cash investments and change in lagged operating assets to the regression of returns on earnings levels and earnings changes examined in Easton and Harris (1991). We argue that a positive coefficient on change in cash investments captures conservatism associated with investments in positive net present value projects the effects of which will not flow into the accounting statements until the expected future benefits are realized. A positive coefficient on change in lagged operating assets implies accounting conservatism associated with the application of accounting rules to operating assets in place. Our empirical results are, in general, consistent with these arguments. We examine differences in conservatism across samples with different market to book ratios, we compare firms with non-negative returns with firms with negative returns, we compare firms reporting losses with firms reporting profits, and we examine firms in different industries, firms with different levels of research and development expenditure, different amounts of depreciation, different amounts of advertising expense, and firms that adopt LIFO inventory valuation compared with those that adopt an alternative to LIFO.JEL Classification: M41     

The Usefulness of Measures of Consistency of Discretionary Components of Accruals in the Detection of Earnings Management

Abstract:  Prior research has shown the prevalence of measurement error in models used to estimate aggregate discretionary accruals. In these models, the incremental information content of the various components of accruals is ignored. Limited prior research and data gathered from firms under Securities and Exchange Commission (SEC) litigation indicate that managers use either one or more than one component of accruals simultaneously, in a consistent way to manipulate bottom-line earnings in a given direction. I propose two measures that capture the consistency between the discretionary components of accruals and test their significance in earnings management (EM) detection in firms that have artificially added accrual manipulation and firms that were targeted by the SEC for accrual manipulation. There is evidence that this information is incrementally useful in detecting EM. This finding paves the way for improvements in the discretionary accruals measure by including consistency information from the components of aggregate accruals.     

Explaining Real Commercial Rents Using an Error Correction Model with Panel Data

This paper presents rent models for retail and office property in the United Kingdom. Panel data are used covering eleven regions for 29 years, enabling us to overcome the limitations of a relatively short time series. We use an error correction model (ECM) framework to estimate long-run equilibrium relationships and short-term dynamic corrections. The combination of panel data and an ECM is an innovative approach that is still being developed in economics. We construct new supply series that combine infrequent stock data with more frequent construction data. Separate regional models are estimated for retail and office properties. The regions are then combined into a number of panels on the basis of the income and price elasticities in the long-run and short-run models. Unlike previous studies, we find no evidence of a board north–south divide between low growth and high growth regions. Like these studies we do find a London effect: in London, demand elasticities for space with respect to both price (rent) and income are much lower in magnitude. We conclude that, while the economic drivers may vary, there is no evidence of differences in the operation of the regional property markets outside London. Elasticities for retail and office are similar. Our final models are parsimonious with single measures of economic activity and of supply and always support the use of an ECM.     

Standard Error Biases When Using Generated Regressors in Accounting Research

We analyze the standard error bias associated with the use of generated regressors—independent variables generated from first-step regressions—in accounting research settings. Under general conditions, generated regressors do not affect the consistency of coefficient estimates. However, commonly used generated regressors can cause standard errors to be understated. Problematic generated regressors include predicted values, coefficient estimates, and measures derived from these estimates. Widely used generated regressors in accounting include measures of earnings persistence, normal accruals, litigation risk, and conditional conservatism. Using simple regression models and simulation, we demonstrate how generated regressors can produce understated standard errors in accounting research settings. We also demonstrate how the magnitude of the standard error bias is inversely related to the precision of the generated regressor. Finally, we discuss bootstrapping as a correction for the bias and demonstrate the pairs cluster bootstrap as a tool to improve inferences in common accounting settings involving generated regressors.     

现行税会关系模式、企业税收差错及税会协调

本文采用2001～2004年的经验数据，分析了沪市公司的税收差错问题。发现我国上市公司税收差错涉及的家数众多、税种多元而且涉税金额巨大，对会计信息质量和国家税收资源及时入缴国库都带来了不利影响。因此，加强会计制度与税收法规的协作，减轻税收差错引致的会计信息失真，维护税收法规的尊严，已是当务之急。     

Neural Networks and Empirical Research in Accounting

This article seeks to provide an overview of the potential role of neural network (connectionist) methodology in empirical accounting research. It highlights how the accounting task domain differs substantially from those for which neural network techniques were originally developed. A non-technical overview of neural network methodology is given, along with guidelines to help accounting researchers interested in applying these new tools to recognise the potential dangers and strengths underlying their use. An illustrative example is provided. The paper suggests research areas in accounting where neural network approaches could make a potential contribution. Explicit recommendations for prospective authors are made.     

The Variability of Earnings and Non-Earnings Information and Earnings Prediction

This paper examines the performance of a 'composite' model of earnings prediction that integrates current earnings and current price as predictors of next year's earnings. The results show that current earnings (current price) play a key role in predicting future earnings when the ratio of earnings variance to price variance is low (high). The composite model is superior to univariate time-series models in out-of-sample predictive accuracy for the overall sample, and is substantially so for the group of firms with a high ratio of earnings variance to price variance.     

Nonparametric Estimation of a Multifactor Heath-Jarrow-Morton Model: An Integrated Approach

We propose a new nonparametric estimator for the volatilitystructure of the zero-coupon yield curve inside the Heath-Jarrow-Mortonframework. The estimator incorporates cross-sectional restrictionsalong the maturity dimension, and also allows for measurementerrors, which can arise from estimation of the yield curve fromnoisy data. The estimates are implemented with daily CRSP bonddata.     

Dividend Covenants and Income Measurement

This paper constructs a theory of dividend restrictions in incomplete markets in an attempt to better understand the role of accounting constructions in optimal dividend restrictions. An entrepreneur, through his company, borrows money from a lender, and repays the debt from a stream of stochastic cash flows. Dividend restrictions are used to balance insolvency costs against the costs of accumulating surplus cash. Of particular concern is whether optimal dividend restrictions can be characterized as defining an accounting-earnings-based reservoir available for dividends, and whether earnings calculated for this purpose exhibit conservatism.     

Bivariate Nonparametric Density Estimation of Stock Prices and Volume

This paper comprehensively investigates the joint movement of stock prices and trading volume of New York and Tokyo stock markets by undertaking nonparametric density estimation. Bivariate nonparametric density estimation has been reported as a powerful tool for revealing complicated relations between two variables. In application to finance, it is important to use a method robust for heavy-tailed densities, since the distributions of asset price changes are known to have heavy tails, and information about sudden and large price changes is contained in the tails. The empirical regularities found in this paper are mostly consistent with previous literature, but partially disagrees with the work of Gallant et al. (1992).     

Does the Measurement of Property and Structural Characteristics Affect Estimated Implicit Prices for Environmental Amenities in a Hedonic Model?

Hedonic models are commonly used to estimate marginal willingness to pay for environmental amenities. These studies utilize variables that are assumed to be measured without error (such as the square footage of the lot or the number of bedrooms) and proxy variables (such as neighborhood or school quality). Lot and structural characteristics may in fact be measured with error. Potential sources of error include inaccurate measures and inconsistent updating. We investigate the effect of using tax-assessor data versus survey data from purchasers to estimate the implicit price of an environmental amenity, lake-water clarity. Convergent validity of the implicit price for water clarity is established if the town and survey data provide statistically indistinguishable estimates of implicit prices for this amenity. Overall, the town-office and survey data on property characteristics were not statistically different in three of the four market groupings examined, which suggests that the traditional municipal sources of these data may not contain substantial measurement error. Furthermore, convergent validity is satisfied in all four market areas. However, differences in computed implicit prices of clarity in two of the market areas are large enough that policy decisions for environmental quality could be affected by the source of the lot and structural data.     

Segment Disclosure and Cost of Capital

We investigate whether segment disclosure influences cost of capital. Improved segment reporting is expected to decrease cost of capital by reducing estimation risk. However, in a competitive environment segment disclosure may also generate uncertainties about future prospects and lead to a larger cost of capital. Asset‐pricing tests confirm that segment disclosure is a priced risk factor. Also, segment disclosure reduces ex‐ante estimates of cost of equity capital and other measures connected to risk. These results suggest a negative relation between segment disclosure and cost of capital. Our results also show that competition reduces, but does not eliminate, the previous relationship.     

Relation Between Predisclosure Information Asymmetry and Trading Volume Reaction Around Quarterly Earnings Announcements

This study investigates the effects of differences in predisclosure information asymmetry on trading volume reaction during quarterly earnings announcements. The analyses show that trading volume reaction to quarterly earnings announcements is positively related to the level of predisclosure information asymmetry and to the magnitude of the price reaction to the announcements. These results are consistent with Kim and Verrecchia's (1991a) theoretical trading volume proposition, and with Atiase and Bamber's (1994) tests of the proposition based on annual earnings announcements. This study also provides evidence on the relation of predisclosure information asymmetry and trading volume before and after quarterly earnings announcements.     

Permanent and Transitory Earnings,Accounting Recording Lag,and the Earnings Coefficient

In this paper, (1) wedefine precisely the terms permanent and transitory earnings;(2) we delineate the effects of the degree of permanence andof accounting recording lag on estimates of the slope coefficientfrom a returns-earnings regression and (3) we examine the relationbetween the estimates of the earnings coefficient and observablevariables that may indicate (i) the extent to which earningsare more or less permanent, and (ii) the extent to which valuerelevant events are recorded in accounting earnings in a timelyfashion. Our main point is that attributing differences in thereturns-earnings relation to one of these effects without controllingfor the other may lead to erroneous conclusions.     

Analysts Earnings Forecasts and the Roles of Earnings and Book Value in Equity Valuation

This study examines the effect of the degree of association between current earnings and expected future earnings on the relative importance of earnings and book value for explaining equity price. Consensus analysts forecasts of one-year-ahead earnings are used to proxy for expected future earnings and are compared to reported current earnings to measure the degree of the association. We find that the value-relevance of current earnings negatively correlates with the extent to which consensus analysts forecasts deviate from current earnings. We also find that the incremental explanatory power of book value for equity price positively correlates with this measure. These results remain robust after controlling for factors known to be affecting the value-relevance of earnings such as negative earnings and the earnings-to-book ratio. Our results also show that this analysts' forecast-based measure of `earnings persistence' dominates historical earnings variance in explaining cross-sectional variations in the value-relevance of earnings and book value.