Testing Homogeneity of Time-Continuous Rating Transitions

Banks could achieve substantial improvements of their portfolio credit risk assessment by estimating rating transition matrices within a time-continuous Markov model, thereby using continuous-time rating transitions provided by internal rating systems instead of discrete-time rating information. A non-parametric test for the hypothesis of time-homogeneity is developed. The alternative hypothesis is multiple structural change of transition intensities, i.e. time-varying transition probabilities. The partial-likelihood ratio for the multivariate counting process of rating transitions is shown to be asymptotically c2 -distributed. A Monte Carlo simulation finds both size and power to be adequate for our example. We analyze transitions in credit-ratings in a rating system with 8 rating states and 2743 transitions for 3699 obligors observed over seven years. The test rejects the homogeneity hypothesis at all conventional levels of significance. --Portfolio credit risk,Rating transitions,Markov model,time-homogeneity,partial likelihood

Testing for Homogeneity in Mixture Models

Statistical models of unobserved heterogeneity are typically formalized as mixtures of simple parametric models and interest naturally focuses on testing for homogeneity versus general mixture alternatives. Many tests of this type can be interpreted as $C(\alpha)$ tests, as in Neyman (1959), and shown to be locally, asymptotically optimal. These $C(\alpha)$ tests will be contrasted with a new approach to likelihood ratio testing for general mixture models. The latter tests are based on estimation of general nonparametric mixing distribution with the Kiefer and Wolfowitz (1956) maximum likelihood estimator. Recent developments in convex optimization have dramatically improved upon earlier EM methods for computation of these estimators, and recent results on the large sample behavior of likelihood ratios involving such estimators yield a tractable form of asymptotic inference. Improvement in computation efficiency also facilitates the use of a bootstrap methods to determine critical values that are shown to work better than the asymptotic critical values in finite samples. Consistency of the bootstrap procedure is also formally established. We compare performance of the two approaches identifying circumstances in which each is preferred

Universal Codes as a Basis for Time Series Testing

We suggest a new approach to hypothesis testing for ergodic and stationary processes. In contrast to standard methods, the suggested approach gives a possibility to make tests, based on any lossless data compression method even if the distribution law of the codeword lengths is not known. We apply this approach to the following four problems: goodness-of-fit testing (or identity testing), testing for independence, testing of serial independence and homogeneity testing and suggest nonparametric statistical tests for these problems. It is important to note that practically used so-called archivers can be used for suggested testing.Comment: accepted for "Statistical Methodology" (Elsevier

The Impact of Aid on Growth Revisited: Do Donor Motives Matter?

The typical identification strategy in aid effectiveness studies assumes donor motives do not influence the impact of aid on growth. We call this homogeneity assumption into question, first constructing a model in which donor motives matter and then testing the assumption empirically.Growth, Aid, Politics

Cosmic homogeneity: a spectroscopic and model-independent measurement

Cosmology relies on the Cosmological Principle, i.e., the hypothesis that the Universe is homogeneous and isotropic on large scales. This implies in particular that the counts of galaxies should approach a homogeneous scaling with volume at sufficiently large scales. Testing homogeneity is crucial to obtain a correct interpretation of the physical assumptions underlying the current cosmic acceleration and structure formation of the Universe. In this Letter, we use the Baryon Oscillation Spectroscopic Survey to make the first spectroscopic and model-independent measurements of the angular homogeneity scale $\theta_{\rm h}$. Applying four statistical estimators, we show that the angular distribution of galaxies in the range 0.46 < z < 0.62 is consistent with homogeneity at large scales, and that $\theta_{\rm h}$ varies with redshift, indicating a smoother Universe in the past. These results are in agreement with the foundations of the standard cosmological paradigm.Comment: 5 pages, 2 figures, Version accepted by MNRA