The Procyclical Effects of Bank Capital Regulation

We assess the procyclical effects of bank capital regulation in a dynamic equilibrium model of relationship lending in which banks are unable to access the equity markets every period. Banks anticipate that shocks to their earnings as well as the cyclical position of the economy can impair their capacity to lend in the future and, as a precaution, hold capital buffers. We find that under cyclically-varying risk-based capital requirements (e.g. Basel II) banks hold larger buffers in expansions than in recessions. Yet, these buffers are insufficient to prevent a significant contraction in the supply of credit at the arrival of a recession. We show that cyclical adjustments in the confidence level underlying Basel II can reduce its procyclical effects on the supply of credit without compromising banks’ long-run solvency targets.Banking regulation;Basel II;Business cycles;Capital requirements;Credit crunch;Loan defaults;Relationship banking

The role of rotation on Petersen Diagrams. The Pi1/0(Omega) Pi_{1/0}(Omega) period ratios

The present work explores the theoretical effects of rotation in calculating the period ratios of double-mode radial pulsating stars with special emphasis on high-amplitude delta Scuti stars (HADS). Diagrams showing these period ratios vs. periods of the fundamental radial mode have been employed as a good tracer of non-solar metallicities and are known as Petersen diagrams (PD).In this paper we consider the effect of moderate rotation on both evolutionary models and oscillation frequencies and we show that such effects cannot be completely neglected as it has been done until now. In particular it is found that even for low-to-moderate rotational velocities (15-50 km/s), differences in period ratios of some hundredths can be found. The main consequence is therefore the confusion scenario generated when trying to fit the metallicity of a given star using this diagram without a previous knowledge of its rotational velocity.Comment: A&A in pres

Bootstrap and Higher-Order Expansion Validity When Instruments May Be Weak

It is well-known that size-adjustments based on Edgeworth expansions for the t-statistic perform poorly when instruments are weakly correlated with the endogenous explanatory variable. This paper shows, however, that the lack of Edgeworth expansions and bootstrap validity are not tied to the weak instrument framework, but instead depends on which test statistic is examined. In particular, Edgeworth expansions are valid for the score and conditional likelihood ratio approaches, even when the instruments are uncorrelated with the endogenous explanatory variable. Furthermore, there is a belief that the bootstrap method fails when instruments are weak, since it replaces parameters with inconsistent estimators. Contrary to this notion, we provide a theoretical proof that guarantees the validity of the bootstrap for the score test, as well as the validity of the conditional bootstrap for many conditional tests. Monte Carlo simulations show that the bootstrap actually decreases size distortions in both cases.

Bootstrap and Higher-Order Expansion Validity When Instruments May Be Weak

It is well-known that size-adjustments based on Edgeworth expansions for the t-statistic perform poorly when instruments are weakly correlated with the endogenous explanatory variable. This paper shows, however, that the lack of Edgeworth expansions and bootstrap validity are not tied to the weak instrument framework, but instead depends on which test statistic is examined. In particular, Edgeworth expansions are valid for the score and conditional likelihood ratio approaches, even when the instruments are uncorrelated with the endogenous explanatory variable. Furthermore, there is a belief that the bootstrap method fails when instruments are weak, since it replaces parameters with inconsistent estimators. Contrary to this notion, we provide a theoretical proof that guarantees the validity of the bootstrap for the score test, as well as the validity of the conditional bootstrap for many conditional tests. Monte Carlo simulations show that the bootstrap actually decreases size distortions in both cases.