Résumé. L'auteur examine comment le risque d'épuisement des obligations fiscales des sociétés avant la déduction des intérêts débiteurs influe sur leur niveau d'endettement. L'étude diffère des travaux précédents sous trois aspects: 1) elle fait usage de données compilées par l'Internal Revenue Service (IRS) à partir des déclarations de revenus des sociétés plutôt que de données comptables; 2) elle mesure le risque d'épuisement de l'impôt avec plus de précision; et 3) elle fait appel à une méthode reposant sur les séries chronologiques et le calcul des différences d'ordre 1, de sorte que les sociétés servent d'élément d'autocontrôle entre années successives. Ces innovations méthodologiques réduisent les distorsions attribuables à l'erreur de mesure et aux variables omises que l'on retrouvait dans les travaux précédents. Les résultats donnent à penser que, toutes choses étant égales par ailleurs, le risque élevé d'épuisement de l'impôt amène les sociétés à réduire leur utilisation du levier financier. L'étude fournit également des données confirmant pour la première fois que les impôts des particuliers influent de manière sensible sur le niveau d'endettement des sociétés. Les effets des décisions relatives au niveau d'endettement sur d'autres variables font également l'objet de tests dont les résultats confirment les prévisions énoncées dans les travaux théoriques précédents.

The study examines how the risk of exhausting corporate tax liabilities before deducting interest expense affects corporate leverage. It differs from prior studies in three ways: (1) it uses data compiled by the Internal Revenue Service (IRS) from corporate tax returns rather than accounting data; (2) it measures risk of tax exhaustion more accurately; and (3) it adopts a first‐difference time‐series approach, so that firms act as their own control between adjacent years. These methodological innovations reduce biases caused by measurement error and omitted variables that were present in prior research. The results suggest that, all else being equal, high risk of tax exhaustion reduces firms' use of leverage. As well, the study provides the first evidence that personal taxes significantly affect corporate leverage. The effects on leverage decisions of other variables are also tested and the results are consistent with predictions from prior theoretical work.

The occurrence of conglomerate mergers is somewhat of a mystery. This paper presents a model demonstrating a tax motive for these mergers. Specifically, conglomerate mergers are unions between firms with not highly correlated earning prospects—when one merger partner underperforms (earning inadequate income) in the future, the other is likely to overperform. By amalgamating such firms into common taxable entities, conglomerate mergers create several tax benefits: (1) improved chances that future tax write‐offs and credits will be immediately utilized in full rather than deferred as less valuable loss‐carryforwards; (2) reduced chances that tax write‐offs and credits are permanently lost in bankruptcy; and (3) an enhanced ability to write off the interest on additional debt Empirical support for these results are presented. Given (1) and (2), the U.S. tax law changes in 1981 and 1986 would respectively encourage and discourage merger activity, outcomes that were indeed observed. Consistent with (3), a cross‐sectional examination of U.S. mergers shows that mergers were more likely to increase consolidated leverage when earnings of the predecessor firms were less highly correlated. Nontax‐related bankruptcy costs are not specifically modeled, but firms whose potential tax write‐offs and credits are larger tend to have lower preference for leverage. Thus, in many instances diminishing bankruptcy risk is not a motive for conglomeration, but full utilization of tax write‐offs is. Résumé. L'occurrence de certaines fusions par conglomérat demeure toujours inexpliquée. L'auteur expose un modèle attribuant les fusions de cette nature à des motifs fiscaux. Selon ce modèle, il en serait ainsi lorsque les fusions par conglomérat touchent des entreprises dont les perspectives de gains ne présentent pas de corrélation très élevée — le rendement escompté de l'une des entreprises qui fusionnent est plutôt mince (ses bénéfices étant insatisfaisants), alors que le rendement escompté de l'autre est assez exceptionnel. Le regroupement de ces entreprises sous forme d'entités imposables grâce à la fusion par conglomérat donnerait lieu, toujours selon ce modèle, aux avantages fiscaux suivants: (1) l'augmentation des chances que les éléments susceptibles d'être passés en charges aux fins de l'impôt ou de donner droit à des dégrèvements soient aussitôt utilisés intégralement plutôt que de faire l'objet de reports de perte prospectifs dont la valeur serait diminuée; (2) la réduction des risques que les éléments susceptibles d'être passés en charges aux fins de l'impôt ou de donner droit à des dégrèvements soient perdus à jamais à la suite d'une faillite; et (3) la possibilité accrue de passer en charges l'intérêt sur la dette supplémentaire. Les constatations empiriques confirment ces hypothèses. Étant donné les hypothèses 1 et 2, les modifications apportées à la loi fiscale aux États‐Unis en 1981 et 1986 encourageraient, dans le premier cas, et décourageraient, dans le second, les fusions, ce qui a été observé dans les faits. Conformément à l'hypothèse 3, un examen transversal des fusions ayant eu lieu aux États‐Unis a démontré qu'elles étaient davantage susceptibles d'augmenter l'effet de levier consolidé lorsque les bénéfices des entreprises constituantes présentaient une corrélation moins élevée. Les coûts des faillites qui ne sont pas d'ordre fiscal ne sont pas spécifiquement intégrés au modèle, mais les entreprises dont les possibilités de passation en charges et de dégrèvements sont plus élevées ont tendance à afficher une préférence moins prononcée pour l'effet de levier. À maints égards, donc, la réduction du risque de faillite n'est pas un motif de fusion par conglomérat, tandis que les possibilités de passation en charges le sont.

We identify a comprehensive list of thirty-eight characteristics for predicting cross-sectional FX options returns. We find that three factors—long-term straddle momentum, implied volatility, and illiquidity—can generate economically and statistically significant risk premia not explained by other return predictors. Meanwhile, the predictability of the other characteristics becomes insignificant after accounting for the FX option three-factor model. The significance of the three factors is confirmed through a series of robustness tests covering different data sources, alternative options strategies, diversification effects, bootstrapping, and omitting crisis years.

Assume data on Nj stock (asset) returns are available for p stocks, allowing us to construct approximate density functions f(xj) for (j=1, 2, …, p) from p empirical cumulative distribution functions (ECDFs). Our portfolio choice is designed to rank ECDF-induced, ill-behaved f(xj) densities subject to multiple modes, asymmetric fat tails, dips, turns, and numerous overlaps. Older portfolio theory assumes that parameters like the mean, variance, and percentiles fully describe f(xj). All six of our algorithms avoid (expected) utility theory. The only available algorithm by Anderson for order-k Stochastic Dominance (SDk) needs a trapezoidal approximation. Our new exact algorithm for SDk is based on ECDFs and overcomes pairwise comparisons. We include algorithms for statistical inference using the bootstrap and one for “pandemic proof” out-of-sample portfolio performance comparisons from our R package ‘generalCorr’. We suggest a test for “zero cost profitable arbitrage” and illustrate our algorithms in action by using two sets of recent 169-month stock returns. We do not claim to suggest new optimal portfolios.

The accuracy of dynamic stress-test capital models remains undocumented. Three methodologies: a CLASS-style approach, Bayesian model averaging, and a Lasso specification are used to forecast the performance of 14 large US banks during the financial crisis. Individual bank models are calibrated using bank historical data while regulatory models are calibrated using representative bank data. Representative bank model forecasts differ dramatically from the forecasts from bank-specific models and from actual outcomes. The Lasso methodology is most accurate, but its superiority may be sample-specific and is only apparent ex post. The results highlight the policy uncertainty inherent in regulatory stress tests.

Multi-year forecasts of bank performance under stressful economic conditions determine large institution regulatory capital requirements and yet the accuracy of these forecasts is undocumented. I compare the accuracies of alternative stress test model forecasts using the financial crisis as the stress scenario. Models include specifications that mimic the Federal Reserve CLASS model and alternatives that use Lasso, the AIC and an abridged set of explanatory variables. A simple single-equation Lasso model has, by far, the best forecast accuracy. Large differences in model forecast accuracy are undetectable from estimation sample statistics. These findings highlight the need for new methods for validating bank stress test models.

This paper examines the interplay among bank liquidity creation (which incorporates all bank on- and off-balance sheet activities), monetary policy, and financial crises. We find that: (1) high liquidity creation (relative to trend) – particularly off-balance sheet liquidity creation – helps predict crises, controlling for other factors; (2) monetary policy has statistically significant, but economically minor effects on liquidity creation by small banks during normal times, and these effects are even weaker during financial crises; (3) monetary policy has very little effects on medium and large bank liquidity creation during both normal times and crises. These findings suggest that authorities may wish to monitor bank liquidity creation closely in order to predict and perhaps lessen the likelihood of financial crises. They might also consider other tools to control bank liquidity creation, such as capital and liquidity requirements.

The efficacy of the Financial Stability Board's proposed requirement for minimum “total loss absorbing capacity” (TLAC) at global systemically important banks (G-SIBs) is assessed using a stylized model of a bank holding company and an equilibrium asset pricing model to value financial claims. I identify a number of G-SIB strategies that satisfy minimum TLAC requirements but fail to reduce implicit safety net subsidies that accrue to G-SIB shareholders or increase the resources available to recapitalize a failing G-SIB subsidiary. To meet the FSB's stated goals, TLAC requirements must impose minimum TLAC at all subsidiaries and restrict how TLAC funds can be invested. An equivalent, but much simpler solution is to significantly increase regulatory capital requirements on systemically important bank subsidiaries.

We model the endogenous emergence of social perceptions about occupations and their impact on occupational choice. In particular, an individual’s social approval increases with his community's perception of his skill in his chosen career. These perceptions vary across communities because individuals better assess the skill of those in occupations similar to their own. Such imperfect assessment can distort choices away from comparative advantage. When skill distributions differ across occupations and/or correlate positively, the community perceives one occupation more favorably. This favored sector experiences overcrowding, but misallocation occurs across both sectors. Furthermore, a positive skill correlation can produce multiple steady states.