We provide evidence about allocations of cash flow freed-up by not paying taxes ("tax-related cash"). Uncertainty about future repayments suggests firms may use tax-related cash more cautiously than other cash flow. We utilize a flow-of-funds model from finance to quantify the relative amounts of tax-related cash associated with various potential uses of operating cash flow. We find that firms allocate tax-related cash differently than other after-tax cash flow. Prior studies find tax avoiders hold more cash, and our results suggest this is because firms invest less (and save more) tax-related cash. We also find that the allocation of tax-related cash varies with relative financial constraints, economic uncertainty, and firms' multinational status in ways consistent with prior findings. For example, firms facing relatively higher levels of financial constraints invest a lower (higher) percentage of tax-related cash in capital expenditures (marketable securities and R&D), possibly to preserve funds for future investment opportunities.

This paper develops a conceptual model that analyzes the impact of increasing market transparency under the Livestock Mandatory Reporting Act of 1999 on the incentives for collusion in the U.S. meatpacking industry. More than likely, meatpackers will have asymmetric priors regarding the distribution of livestock prices. Moreover, they lack the incentives to voluntarily reveal their real priors. Thus, the enforcer of the Act faces a problem of asymmetric information regarding the informativeness of publicly disclosed market reports relative to that of packers' priors. Analytical results predict that divergent priors of Bayesian packers can be updated by more informative market reports, so that the resultant posteriors converge, enabling packers to identify a more efficient, unanimous trigger price. This enhances observability of deviations from collusive behavior, and increases the internal policing efficiency by a cartel that employs trigger price strategies to monitor deviations by its members. Contrary to the Act's well-intended objectives, this is consistent with promoting collusion and decreasing market efficiency.

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In this paper, we propose and empirically test a cross-sectional profitability forecasting model which incorporates two major improvements relative to extant models. First, in terms of model construction, we incorporate mean reversion through the use of a twostage partial adjustment model and inclusion of a number of additional relevant determinants of profitability. Second, in terms of model estimation, we employ least absolute deviation (LAD) analysis instead of ordinary least squares because the former approach is able to better accommodate outliers. Results reveal that forecasts from our model are more accurate than three extant models at every forecast horizon considered and more accurate than consensus analyst forecasts at forecast horizons of two through five years. Further analysis reveals that LAD estimation provides the greatest incremental accuracy improvement followed by the inclusion of income subcomponents as predictor variables, and implementation of the two-stage partial adjustment model. In terms of economic relevance, we find that forecasts from our model are informative about future returns, incremental to forecasts from other models, analysts' forecasts, and standard risk factors. Overall, our results are important because they document the increased accuracy and economic relevance of a cross-sectional profitability forecasting model which incorporates improvements to extant models in terms of model construction and estimation.Les auteurs proposent et testent de fac ßon empirique un mod ele pr evisionnel de rentabilit e transversal comportant deux am eliorations importantes par rapport aux mod eles existants. En premier lieu, au chapitre de la structure du mod ele, les auteurs incorporent la r egression a la moyenne en utilisant un mod ele d'ajustement partiel a deux paliers et plusieurs d eterminants pertinents suppl ementaires de la rentabilit e. En second lieu, au chapitre de l'estimation du mod ele, les auteurs, plutôt que d'appliquer la m ethode classique des moindres carr es, ont recours a l'analyse du moindre ecart absolu parce qu'elle permet de mieux traiter les valeurs extrêmes. Ils constatent que les pr evisions produites par leur mod ele sont plus exactes que celles de trois mod eles existants, et cela pour tous les horizons pr evisionnels du plan de recherche, et qu'elles sont egalement plus exactes que les pr evisions consensuelles des analystes, pour les horizons pr evisionnels de deux a cinq ans. Une analyse plus pouss ee indique que l'estimation du moindre ecart absolu procure l'am elioration marginale la plus importante de l'exactitude, suivie de l'inclusion des sous-el ements du revenu a titre de variables ind ependantes et de l'emploi du mod ele d'ajustement partiel a deux paliers. Pour ce qui est de la pertinence economique, les auteurs observent que les pr evisions produites par leur mod ele sont plus r ev elatrices des rendements futurs que celles que fournissent les autres mod eles, que les pr evisions des analystes et que les facteurs de risque standard. Dans l'ensemble...

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