ABSTRACT Errors and bias are both inherent features of accounting. In theory, while errors discourage bias by lowering the value relevance of accounting, they can also facilitate bias by providing camouflage. Consistent with theory, we find a hump‐shaped relation between a firm's propensity to engage in intentional misstatement and the prevalence of unintentional misstatements in the firm's industry for the whole economy and a majority of the industries. The result is robust to using firms’ number of items in financial statements and exposure to complex accounting rules as alternative proxies for errors and to using the restatement amount in net income to quantify the magnitude of bias and errors. To directly test for the two effects of errors, we show that when errors are more prevalent, the market reacts less to firms’ earnings surprises and bias is more difficult to detect. Our results highlight the imperfectness of accounting, advance understanding of firms’ reporting incentives, and shed light on accounting standard setting.

Abstract Trust is often posited to substitute for management control in interfirm transactions. However, this raises questions of how trust arises in new relationships, and whether trust that is not based on prior experience transacting together is sufficient to persuade managers to forgo investments in management controls. We use an experiment to test whether two features of the early stage of an interfirm relationship influence a buyer's initial trust in a supplier and have consequences for subsequent investments in management controls and in the collaboration. These two features are the autonomy of the buyer's manager to choose a supplier (i.e., delegation of decision‐making authority) and the supplier's willingness to share information with the buyer. We find that the buyer manager's initial trust in the supplier is associated positively with both the autonomy to choose the supplier and the supplier's willingness to share information. Information content and supplier characteristics are held constant, so these results are novel and distinct from prior studies of the antecedents of trust. We find that higher initial trust is associated with reduced expenditures for management controls and increased investments in the collaboration. Thus, we conclude that delegation of decision‐making authority and supplier information‐sharing behavior in the early stages of a relationship influence the formation of initial trust, which has real consequences for investments in management control and in the collaboration.

This paper links the CEO's concerns for the current stock price to reductions in real investment. We identify short-term concerns using the amount of stock and options scheduled to vest in a given quarter. Vesting equity is associated with a decline in the growth of research and development and capital expenditure, positive analyst forecast revisions, and positive earnings guidance, within the same quarter. More broadly, by introducing a measure of incentives that is determined by equity grants made several years prior, and thus unlikely driven by current investment opportunities, we provide evidence that CEO contracts affect real decisions.

Many researchers use the G-index or E-index to measure firms’ takeover defenses. Others argue that these indices are not related to firms’ takeover likelihoods. We find that, unlike their raw values, the instrumented versions of these indices are significantly and negatively related to acquisition likelihood. The difference between the raw and instrumented results indicates that the G-index and E-index include an endogenous component and highlights the importance of accounting for endogeneity in tests that use takeover indices to measure takeover deterrence. We provide data on new instruments that researchers can use to address these issues.Received April 13, 2016; editorial decision October 14, 2016 by Editor David Dennis.

We design an experiment to test the hypothesis that, in violation of Bayes’ rule, some people respond more forcefully to the strength of information than to its weight. We provide incentives to motivate effort, use naturally occurring information, and control for risk attitude. We find that the strength–weight bias affects expectations but that its magnitude is significantly lower than originally reported. Controls for nonlinear utility further reduce the bias. Our results suggest that incentive compatibility and controls for risk attitude considerably affect inferences on errors in expectations.

John Formby, Terry Seaks, and W. Smith (hereafter FSS) argue that the P-Gini coefficient is affected by the arbitrary choice of the age to a degree which brings the validity of [the] age-related measure into question (FSS, 1989, p. 2). More pointedly, a sufficiently narrow age partition, the P-curve can always be driven to the L-curve. Convergence [of the P-Gini] to a nonzero estimate does not occur... (p. 4). These conclusions I believe result from a misapplication of Gastwirth's theorem on disaggregation, and a failure to observe statistical rules relating to sample size and sampling error. I will show that when these rules are observed, the value of the P-Gini does not converge to zero but properly reflects the relative importance of the nonlife-cycle factors affecting the distribution. When calculating the traditional L-Gini, the more disaggregation the better; the number and accuracy of the sample points are the only consideration since all are thrown into one conceptual box and compared in terms of income size. But if we try to identify the factors which account for income inequality in terms of age versus nonage related factors, we are setting up two conceptual boxes (the age-Gini and the P-Gini) and we are no longer simply dealing with a Gastwirth-type problem. Statistical considerations come into play; for example, we must have a sufficient number of sample points in each conceptual box in order to give a reliable estimate of the importance of each factor. The key-allocating device which I employ is the age-Gini, derived from the average age-income profile. The age-Gini shows the amount of inequality that would exist if all nonage-related sources of inequality were eliminated. When calculating this coefficient, the means of the age-groups are used in order to wash out all random and nonagerelated influences, but this separating device works well only if the means are based on large samples. Otherwise, sampling errors create spurious variation and impart an upward bias to the value of the age-Gini. FSS (p. 4) drive the age-Gini value up to the L-Gini by increasing the number of agegroups until they equal the number in the sample. Since the means of the age-groups are now based on samples of one, they become as erratic as the individual incomes, and impart the maximum upward bias to the age-Gini. It is true that the age-income profile (and the age-Gini) are conceptually refined by using smaller age intervals, but unless sample size is large compared to the number of age intervals, the gains from conceptual purification will be more than offset by the greater sampling errors of the age means. This kind of limitation is shared by many other statistical measures which do not thereby lose their validity or usefulness. Under what conditions will the true or limiting value of the P-Gini emerge? FSS in their footnote 3 state that there is no limiting value other than zero. Let us test this claim. Assume we have a scatter diagram of income (Y) and age (X), and wish to show average income in relation to age. We start with a finite number of age-groups and plot their mean incomes on the diagram. By continuously reducing the age interval and increasing sample size, we end up with a curve passing through the true means of infinitely small age intervals: this defines the average age-income profile. Since for each person we have data on income and age, we can with this curve (or an approximation of it) calculate the age-Gini and L-Gini without grouping for age or income. The age-income curve allows us to determine the mean income (u) at any given age and for all persons. *Department of Economics, Portland State University, P.O. Box 751, Portland, OR 97207.

We demonstrate the central importance of creditors’ ability to use movable assets as collateral (as distinct from immovable real estate) when borrowing from banks. Using a unique cross-country micro-level loan data set containing loan-to-value ratios for different assets, we find that loan-to-values of loans collateralized with movable assets are lower in countries with weak collateral laws, relative to immovable assets, and that lending is biased toward the use of immovable assets. Using sector-level data, we find that weak movable collateral laws create distortions in the allocation of resources that favor immovable-based production and investment. An analysis of Slovakia's collateral law reform confirms our findings.

This paper examines the long-term impacts of in-utero and early childhood exposure to ambient air pollution on adult labor market outcomes. We take advantage of a new administrative data set that is uniquely suited for addressing this question because it combines information on individuals ’ quarterly earnings together with their counties and dates of birth. We use the sharp changes in ambient air pollution concentrations driven by the implementation of the 1970 Clean Air Act Amendments as a source of identifying variation, and we compare cohorts born in counties that experienced large changes in total suspended particulate (TSP) exposure to cohorts born in counties that had minimal or no changes. We find a significant relationship between TSP exposure in the year of birth and adult labor market outcomes. A 10 unit decrease in TSP in the year of birth is associated with a 1 percent increase in annual earnings for workers aged 29-31. Most, but not all, of this effect is driven by an increase in labor force participation. In present value, the gains from being born into a county affected by the 1970 Clean Air Act amount to about $4,300 in lifetime income for the 1.5 million individuals born into

1) That their equation (2) is logically equivalent to our (hereafter, D-K) sufficiency conditions presented in the 1974 issue of this Review. 2) That the assumption of degree zero homogeneity (in the variables m and p) of the utility function serves completely to characterize the class of illusion-free demand functions derivable from ordinal utility theory. 3) That it is possible to reinstate the usual Slutsky properties by adopting the semi-separable utility function given in their equation (4).