Forecasting Risk in Earnings

Conventional measures of risk in earnings based on historical standard deviation require long time‐series data and are inadequate when the distribution of earnings deviates from normality. We introduce a methodology based on current fundamentals and quantile regression to forecast risk reflected in the shape of the distribution of future earnings. We derive measures of dispersion, asymmetry, and tail risk in future earnings using quantile forecasts as inputs. Our analysis shows that a parsimonious model based on accruals, cash flows, special items, and a loss indicator can predict the shape of the distribution of earnings with reasonable power. We provide evidence that out‐of‐sample quantile‐based risk forecasts explain incrementally analysts' equity and credit risk ratings, future return volatility, corporate bond spreads, and analyst‐based measures of future earnings uncertainty. Our study provides insights into the relations between earnings components and risk in future earnings. It also introduces risk measures that will be useful for participants in both the equity and credit markets.     

Bridging the gap between accounting and finance

I suggest that the separation of the academic disciplines of accounting and finance has had some detrimental consequences for the development of research and practice in both disciplines, and especially in finance. I argue that an understanding of financial statement numbers and the accounting principles on which they depend – the accounting microstructure – can be important in developing better valuation and asset pricing models and in identifying relevant dimensions of risk. Therefore finance research can benefit from assimilating recent advances in accounting research. Similarly, accounting research relevant to valuation and asset pricing can benefit by adopting theoretical perspectives and empirical methods from finance research.     

Cross‐border information transfers: Evidence from profit warnings issued by European firms

This paper reports evidence on cross‐border accounting information transfers associated with profit warning announcements. Using a sample of firms from 29 European countries, we find that negative earnings surprises disclosed by firms in one country affect investors’ perceptions of comparable non‐announcing firms in other countries. The form and magnitude of cross‐border effects is consistent with domestic transfers. Tests explaining variation in cross‐border information transfers provide some (albeit rather limited) evidence that effects vary according to a range of firm‐, industryand country‐level characteristics.     

Adherence to environmental law: the strategic complementarities of compliance decisions

In this paper we address why firms comply with environmental regulations when enforcement is weak by suggesting that firms choose their level of environmental compliance strategically. Our theoretical model shows that compliance decisions among firms are strategic complements—increased compliance by one firm will positively influence the compliance rate of its rival. In our empirical analysis we find that the compliance rates of other regulated entities have a positive and significant effect on a regulated source's compliance behavior in three of our four heavily regulated industries. If compliance decisions are strategic complements, this may partially explain high compliance rates in the presence of limited regulatory pressure.     

Interpreting DNA Evidence: A Review

The paper provides a review of current issues relating to the use of DNA profiling in forensic science. A short historical section gives the main statistical milestones that occurred during a rapid development of DNA technology and operational uses. Greater detail is then provided for interpretation issues involving STR DNA profiles, including:

• – methods that take account of population substructure in DNA calculations;

• – parallel work carried out by the US National Research Council;

• – the move away from multiple independence testing in favour of experiments that demonstrate the robustness of casework procedures;

• – the questionable practice of source attribution 'with reasonable scientific certainty';

• – the effect on the interpretation of profiles obtained under increasingly sensitive techniques, the LCN technique in particular;

• – the use of DNA profiles as an intelligence tool;

• – the interpretation of DNA mixtures.

Experience of presenting DNA evidence within UK courts is also discussed. The paper then summarises a generic interpretation framework based on the concept of likelihood ratio within a hierarchy of propositions. Finally the use of Bayesian networks to interpret DNA evidence is reviewed.     

Stochastic specification of production functions and economic implications

The stochastic specification of input-output response is examined. Postulates are set forth which seem reasonable on the basis of a priori theorizing and observed behavior. It is found that commonly used formulations are restrictive and may lead to inefficient and biased results. A function which satisfies the postulates is suggested. Two- and four-stage procedures for estimation of the resulting function are then outlined. The estimators are shown to be consistent and, in the latter case, asymptotically efficient under normality.     

A general equilibrium model of production with a random marginal rate of substitution

This paper examines the qualitative effects of risk aversion in a two-sector general equilibrium model where uncertainty is due to random production in one of the sectors. Technology is more general than used previously and provides for a random marginal rate of substitution. Also, the possibility that risk is decreasing in factor usage is considered. Results show that earlier qualitative conclusions on the effects of changing risk may be reversed under these cases.     

Experimental Evidence for Attractions to Chance

Divide the decision-maker's future into: (i) a pre-outcome period (lasting from the decision until the outcome of that decision is known), and (ii) a sequel post-outcome period (beginning when the outcome becomes known). Anticipated emotions in both periods may influence the decision, in particular, with regard to an outcome that matters to the person, the enjoyable tension from not yet knowing what this outcome will be. In the experiments presented, lottery choice can be explained by this attraction to chance, and cannot be explained by either convex von Neumann–Morgenstern utility, or by rank-dependent risk-loving weights: attraction to chance is a separate motivator.