The delta method and continuous mapping theorem are among the most extensively used tools in asymptotic derivations in econometrics. Extensions of these methods are provided for sequences of functions that are commonly encountered in applications and where the usual methods sometimes fail. Important examples of failure arise in the use of simulation-based estimation methods such as indirect inference. The paper explores the application of these methods to the indirect inference estimator (IIE) in first order autoregressive estimation. The IIE uses a binding function that is sample size dependent. Its limit theory relies on a sequence-based delta method in the stationary case and a sequence-based implicit continuous mapping theorem in unit root and local to unity cases. The new limit theory shows that the IIE achieves much more than (partial) bias correction. It changes the limit theory of the maximum likelihood estimator (MLE) when the autoregressive coefficient is in the locality of unity, reducing the bias and the variance of the MLE without affecting the limit theory of the MLE in the stationary case. Thus, in spite of the fact that the IIE is a continuously differentiable function of the MLE, the limit distribution of the IIE is not simply a scale multiple of the MLE, but depends implicitly on the full binding function mapping. The unit root case therefore represents an important example of the failure of the delta method and shows the need for an implicit mapping extension of the continuous mapping theorem.

Recent cases of hedge fund fraud have caused large losses for investors and have fueled the debate regarding the ability of regulators to oversee the industry. This article proposes a set of performance flags, based on suspicious patterns in returns, as indicators of a heightened risk of fraud. We collect a sample of hedge funds charged with legal or regulatory violations and find that funds charged with misappropriation, overvaluation, misrepresentation, or Ponzi schemes trigger the performance flags at a higher frequency than other funds.

We show how the change to differential voting rights allows dominant shareholders to retain control even after selling substantial economic ownership in the firm and diversifying their wealth. This unbundling of cash flow and control rights leads to more dispersed economic ownership and a closer alignment of dominant and dispersed shareholder interests. When insiders sell sizeable amounts of their economic interests, firms increase capital expenditures, strengthen corporate focus, divest non-core operations, and generate superior industry-adjusted performance. The change to differential voting rights both fosters corporate control activity and creates higher takeover premiums that are paid equally to all shareholders.

The financial crisis prompted widespread interest in developing a better understanding of how capital regulation drives bank behavior. This paper uses a unique, comprehensive database of regulatory capital requirements on all UK banks to examine their effects on capital, lending and balance sheet management behavior. We find that capital requirements that include firm-specific, time-varying add-ons set by supervisors affect banks’ desired capital ratios and that resulting adjustments to capital and lending depend on the gap between actual and target ratios. We use these results to measure the effects of a capital regime that includes features similar to those embedded in the UK framework. Our results suggest that countercyclical capital requirements may be less effective in slowing credit activity when banks can readily satisfy them with lower-quality (lower-costing) capital elements versus higher-quality common equity. Given the size of the UK banking sector and the global nature of many of the largest institutions in the UK banking sector, the results have implications for the ongoing debate surrounding the design and calibration of international capital standards.

The impact of undiversified idiosyncratic risk on value-at-risk and expected shortfall can be approximated analytically via a methodology known as granularity adjustment (GA). In principle, the GA methodology can be applied to any risk-factor model of portfolio risk. Thus far, however, analytical results have been derived only for simple models of actuarial loss, i.e., credit loss due to default. We demonstrate that the GA is entirely tractable for single-factor versions of a large class of models that includes all the commonly used mark-to-market approaches. Our approach covers both finite ratings-based models and models with a continuum of obligor states. We apply our methodology to CreditMetrics and KMV Portfolio Manager, as these are benchmark models for the finite and continuous classes, respectively. Comparative statics of the GA reveal striking and counterintuitive patterns. We explain these relationships with a stylized model of portfolio risk.

Expert agents, such as lawyers, play a prominent role in conflict resolution, yet little is known about how they affect outcomes. We construct a model that permits us to estimate the influence of agents and test whether the parties in a dispute face prisoner's dilemma incentives. Using eighteen years of final-offer arbitration data from New Jersey, we find the parties do significantly better when they retain agents and that the parties learn about this benefit over time. However, we also find that the gain to using an agent is fully offset when the opposing party also hires an agent. Since agents are costly, this noncooperative equilibrium is Pareto inferior.

We propose a new inverse probability weighting (IPW) estimator for moment condition models with missing data. Our estimator is easy to implement and compares favourably with existing IPW estimators, including augmented IPW estimators, in terms of efficiency, robustness, and higher-order bias. We illustrate our method with a study of the relationship between early Black–White differences in cognitive achievement and subsequent differences in adult earnings. In our data set, the early childhood achievement measure, the main regressor of interest, is missing for many units.

Using a comprehensive data set of all U.S. investment in foreign equities, we find that the single most important determinant of the amount of U.S. investment a foreign firm receives is whether the firm cross‐lists on a U.S. exchange. Correcting for selection biases, cross‐listing leads to a doubling (or more) in U.S. investment, an impact greater than all other factors combined. Much of this increased U.S. investment is purchased in the foreign market, implying that the cross‐listing effect reflects something more fundamental about a firm than easier acquisition of its securities. We also demonstrate that cross‐listing is an important determinant of U.S. international investment at the country level and describe easy‐to‐implement methods for including a cross‐listing variable as an endogenous control.

The article develops a new theory of pricing to market driven by dynamic frictions of building market shares. Our key innovation is a capital theoretic model of marketing in which relations with customers are valuable. We discipline the introduced friction using data on differences between short-run and long-run price elasticity of international trade flows. We show that the model accounts for several pricing “puzzles” of international macroeconomics.

Innovations to consumer confidence convey incremental information about economic activity far into the future. Does this reflect a causal effect of animal spirits on economic activity, or news about exogenous future productivity received by consumers? Using indirect inference, we study the impulse responses to confidence innovations in conjunction with an appropriately augmented New Keynesian model. While news, animal spirits, and pure noise all contribute to confidence innovations, the relationship between confidence and subsequent activity is almost entirely reflective of the news component. Confidence innovations are well characterized as noisy measures of changes in expected productivity growth over a relatively long horizon.