Fisher’s pivot functions (PFs) continue to dominate statistical inference and bootstrap literature, despite Efron and Hinkley and Royall’s attempts to inject robustness. Vinod uses Godambe’s pivot functions (GPFs) based on Godambe—Durbin estimating functions (EFs) to develop numerically computed GPF roots. Such GPF roots can fill a long-standing need in the bootstrap literature for robust pivot...

In banking the default behavior of the counterpart is of interest not only for the pricing of transactions under credit risk but also for the assessment of portfolio credit risk. We develop a test against the hypothesis that default intensities are constant over time within a homogeneous group of counterparts under investigation, e.g. a rating class. The Kolmogorov-Smirnov-type test builds on t...

This paper uses a functional coefficient regression to estimate time-varying betas and alphas in the conditional capital asset pricing model. Functional coefficient representation relaxes the strict assumptions on the structure of betas and alphas by combining the predictors into an index that best captures time variations in betas and alphas and estimates them nonparametrically. This index in ...

This paper presents a Markov chain Monte Carlo (MCMC) algorithm to estimate parameters and latent stochastic processes in the asymmetric stochastic volatility (SV) model, in which the Box-Cox transformation of the squared volatility follows an autoregressive Gaussian distribution and the marginal density of asset returns has heavytails. To test for the significance of the Box-Cox transformation...

Inventory fluctuations are an important phenomenon in business cycles. However, the preliminary data on inventory investment as published in the German national accounts are tremendously prone to revision and therefore ill-equipped to diagnose the current stance of the inventory cycle. The Ifo business survey contains information on the assessments of inventory stocks in manufacturing as well a...

Misspecification Testing in a Class of Conditional Distributional Models We propose a specification test for a wide range of parametric models for the conditional distribution function of an outcome variable given a vector of covariates. The test is based on the Cramer-von Mises distance between an unrestricted estimate of the joint distribution function of the data, and a restricted estimate t...

This paper proposes a formal model selection test for choosing between two competing structural econometric models. The procedure is based on a novel lack-oft criterion, namely, the simulated mean squared error of predictions (SMSEP), taking into account the complexity of structural econometric models. It is asymptotically valid for any xed number of simulations, and allows for any estimator wh...

This paper shows that out-of-sample forecast comparisons can help prevent data mining-induced overfitting. The basic results are drawn from simulations of a simple Monte Carlo design and a real data-based design similar to those in Lovell (1983) and Hoover and Perez (1999). In each simulation, a general-to-specific procedure is used to arrive at a model. If the selected specification includes a...

We develop two specification tests of predictive densities based on that the generalized residuals of correctly specified predictive density models are i.i.d. uniform. The simultaneous test compares the joint density of generalized residuals with product of uniform densities; the sequential test examines the hypotheses of serial independence and uniformity sequentially based on the copula repre...

Matching estimators are widely used for the evaluation of programs or treatments. Often researchers use bootstrapping methods for inference. However, no formal justification for the use of the bootstrap has been provided. Here we show that the bootstrap is in general not valid, even in the simple case with a single continuous covariate when the estimator is root-N consistent and asymptotically ...